Pedons & Water Table Along Wetland to Upland Gradient
Anthony Stewart
## [1] "ATTRIBUTE" "WETLAND_TY" "ACRES" "Shape_Leng" "Shape_Area"
## # A tibble: 9 × 2
## hpu result
## <fct> <dbl>
## 1 Bh 0.148
## 2 Bhs 0.0447
## 3 Bhsm 0.0616
## 4 Bi 0.0750
## 5 E 0.0643
## 6 H 0.503
## 7 I 0.193
## 8 O 0.0280
## 9 T 0.0612
## Warning: Removed 4 rows containing non-finite values (`stat_ydensity()`).
## Warning: Groups with fewer than two data points have been dropped.
## Warning: Removed 4 rows containing missing values (`geom_point()`).
Is there a model?
##
## Call:
## lm(formula = WET ~ hpu, data = hb_pedons_ext)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19318 -0.06195 -0.04470 0.00085 0.74792
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.14808 0.01844 8.029 1.55e-14 ***
## hpuBhs -0.10339 0.02941 -3.515 0.000498 ***
## hpuBhsm -0.08648 0.05249 -1.648 0.100330
## hpuBi -0.07308 0.02750 -2.657 0.008246 **
## hpuE -0.08379 0.03514 -2.385 0.017634 *
## hpuH 0.35492 0.11142 3.185 0.001577 **
## hpuI 0.04509 0.04196 1.075 0.283294
## hpuO -0.12008 0.03934 -3.052 0.002445 **
## hpuT -0.08693 0.02392 -3.634 0.000322 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1554 on 346 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.1119, Adjusted R-squared: 0.09132
## F-statistic: 5.447 on 8 and 346 DF, p-value: 1.759e-06
## Analysis of Variance Table
##
## Response: WET
## Df Sum Sq Mean Sq F value Pr(>F)
## hpu 8 1.0524 0.13155 5.4471 1.759e-06 ***
## Residuals 346 8.3558 0.02415
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Warning: Removed 1 rows containing non-finite values (`stat_ydensity()`).
## Warning: Removed 1 rows containing missing values (`geom_point()`).
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 30 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 30 rows containing missing values (`geom_point()`).
Is there a model in W3?
##
## Call:
## lm(formula = WET ~ hpu, data = w3_pedons_ext)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.12298 -0.04011 -0.01673 0.01687 0.25955
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.116994 0.034248 3.416 0.00184 **
## hpuBhs podzol -0.066107 0.048434 -1.365 0.18244
## hpuBimodal podzol -0.087680 0.076582 -1.145 0.26130
## hpuE podzol -0.078464 0.050134 -1.565 0.12805
## hpuLithic Histosol -0.088856 0.052315 -1.698 0.09977 .
## hpuTypical podzol 0.007971 0.055224 0.144 0.88620
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.09687 on 30 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.1668, Adjusted R-squared: 0.02797
## F-statistic: 1.201 on 5 and 30 DF, p-value: 0.3323
## Analysis of Variance Table
##
## Response: WET
## Df Sum Sq Mean Sq F value Pr(>F)
## hpu 5 0.05637 0.0112739 1.2015 0.3323
## Residuals 30 0.28151 0.0093836##
## Call:
## lm(formula = WET ~ water_table, data = w3_pedons_ext)
##
## Residuals:
## 3 6 11 17 19 28 35
## -0.11031 -0.06748 -0.04230 0.02109 0.25246 -0.03985 -0.01360
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1561297 0.1427138 1.094 0.324
## water_table -0.0008764 0.0024205 -0.362 0.732
##
## Residual standard error: 0.13 on 5 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.02555, Adjusted R-squared: -0.1693
## F-statistic: 0.1311 on 1 and 5 DF, p-value: 0.7321
## Analysis of Variance Table
##
## Response: WET
## Df Sum Sq Mean Sq F value Pr(>F)
## water_table 1 0.002215 0.0022146 0.1311 0.7321
## Residuals 5 0.084466 0.0168931Watershed 3 wells
Other soil moisture data
## plot WET
## 1 IL1 0.0097815807
## 2 IL2 0.0004923271
## 3 IL3 0.0005539354
## 4 IH1 0.0056223716
## 5 IH2 0.2645237349
## 6 IH3 0.0014275625
## 7 E01 0.0253475973
## 8 E02 0.0003309475
## 9 E03 0.0066819036
## 10 E07 0.0005119858
## 11 E08 0.0108769163
## 12 E09 0.0097710399
## 13 E10 0.2717093112
## 14 E12 0.0008666217
## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
## Warning: Removed 7674 rows containing non-finite values (`stat_smooth()`).
## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
## Warning: Removed 19943 rows containing non-finite values (`stat_smooth()`).
## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
## Warning: Removed 32704 rows containing non-finite values (`stat_smooth()`).
## `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
## Warning: Removed 15780 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 32704 rows containing missing values (`geom_point()`).
## Warning: Removed 19943 rows containing missing values (`geom_point()`).
## Warning: Removed 7674 rows containing missing values (`geom_point()`).
## Warning: Removed 15780 rows containing missing values (`geom_point()`).
Old Denitrification soil moisture & oxygen
## ID UPL WET
## 1 1 0.9957921 0.004207876
## 2 2 0.9984806 0.001519438
## 3 3 0.9716969 0.028303088
## Warning: Removed 1 rows containing missing values (`geom_point()`).
## Removed 1 rows containing missing values (`geom_point()`).
## Removed 1 rows containing missing values (`geom_point()`).
## Warning: Removed 26 rows containing missing values (`geom_point()`).
## Warning: Removed 1 rows containing missing values (`geom_point()`).
## Warning: Removed 91 rows containing missing values (`geom_point()`).
## Warning: Removed 1 rows containing missing values (`geom_point()`).
## Removed 1 rows containing missing values (`geom_point()`).
## Removed 1 rows containing missing values (`geom_point()`).
## Warning: Removed 206 rows containing missing values (`geom_point()`).
## Warning: Removed 59 rows containing missing values (`geom_point()`).
